Detecting Software Errors via Genetic Algorithms

According to a current study from the University of Cambridge, software developers are spending about the half of their time on detecting errors and resolving them. Projected onto the global software industry, according to the study, this would amount to a bill of about 312 billion US dollars every year. "Of course, automated testing is cheaper", explains Andreas Zeller, professor of Software Engineering at Saarland University, as you could run a program a thousand times without incurring any charges. "But where do these necessary test cases come from?" asks Zeller. "Generating them automatically is tough, but thinking of them yourself is even tougher."

In cooperation with the computer scientists Nikolas Havrikov and Matthias Höschele, he has now developed the software system "XMLMATE". It generates test cases automatically and uses them to test the given program code automatically. What is special about it is that the only requirement the program to be tested has to meet is that its input must be structured in a certain way, since the researchers use it to generate the initial set of test cases. They feed them to the so-called genetic algorithm on which the testing is based. It works similarly to biological evolution, where the chromosomes are operating as the input. Only the input that covers a significant amount of code which has not been executed yet survives. As Nikolas Havrikov explains their strategy: "It is not easy to detect a real error, and the more code we are covering, the more sure we can be that more errors will not occur." Havrikov implemented XMLMATE. "As we use the real existing input interface, we make sure that there are no false alarms: Every error found can also happen during the execution of the program," adds Zeller.

The researchers have unleashed their software on open source programs users are already working with in daily life. With their program they detected almost twice as many fatal errors as similar test methods that only work with randomly generated input. "But the best thing is that we are completely independent from the application area. With our framework, we are not only able to test computer networks, the processing of datasets, websites or operating systems, but we can also examine software for sensors in cars," says Zeller.

The computer scientists in Saarbrücken developed XMLMATE in the Java programming language. The input for the software to test is defined according to the description language XML, so the existence of a XML schema is helpful. Since XML is standardized and considered as a kind of world language between input formats, most of the programming input fits XMLMATE and if not, it can be quickly converted to do so with the corresponding tools.

The Department of Computer Science represents the center of computer science research in Saarbrücken. Seven other worldwide renowned research institutes are close by the department: The Max Planck Institutes for Informatics and for Software Systems, the German Research Center for Artificial Intelligence (DFKI), the Center for Bioinformatics, the Intel Visual Computing Institute, the Center for IT Security, Privacy and Accountability (CISPA) and the Cluster of Excellence "Multimodal Computing and Interaction".

Most Popular Now

Stepping Hill Hospital Announced as SPAR…

Stepping Hill Hospital, part of Stockport NHS Foundation Trust, has replaced its bedside units with state-of-the art devices running a full range of information, engagement, communications and productivity apps, to...

DMEA 2025: Digital Health Worldwide in B…

8 - 10 April 2025, Berlin, Germany. From the AI Act, to the potential of the European Health Data Space, to the power of patient data in Scandinavia - DMEA 2025...

Is AI in Medicine Playing Fair?

As artificial intelligence (AI) rapidly integrates into health care, a new study by researchers at the Icahn School of Medicine at Mount Sinai reveals that all generative AI models may...

New System for the Early Detection of Au…

A team from the Human-Tech Institute-Universitat Politècnica de València has developed a new system for the early detection of Autism Spectrum Disorder (ASD) using virtual reality and artificial intelligence. The...

Generative AI's Diagnostic Capabili…

The use of generative AI for diagnostics has attracted attention in the medical field and many research papers have been published on this topic. However, because the evaluation criteria were...

Diagnoses and Treatment Recommendations …

A new study led by Prof. Dan Zeltzer, a digital health expert from the Berglas School of Economics at Tel Aviv University, compared the quality of diagnostic and treatment recommendations...

AI Tool can Track Effectiveness of Multi…

A new artificial intelligence (AI) tool that can help interpret and assess how well treatments are working for patients with multiple sclerosis (MS) has been developed by UCL researchers. AI uses...

Surrey and Sussex Healthcare NHS Trust g…

Surrey and Sussex Healthcare NHS Trust has marked an important milestone in connecting busy radiologists across large parts of South East England, following the successful go live of Sectra's enterprise...

Dr Jason Broch Joins the Highland Market…

The Highland Marketing advisory board has welcomed a new member - Dr Jason Broch, a GP and director with a strong track record in the NHS and IT-enabled transformation. Dr Broch...

DMEA 2025 Ends with Record Attendance an…

8 - 10 April 2025, Berlin, Germany. DMEA 2025 came to a successful close with record attendance and an impressive program. 20,500 participants attended Europe's leading digital health event over the...

Multi-Resistance in Bacteria Predicted b…

An AI model trained on large amounts of genetic data can predict whether bacteria will become antibiotic-resistant. The new study shows that antibiotic resistance is more easily transmitted between genetically...

AI-Driven Smart Devices to Transform Hea…

AI-powered, internet-connected medical devices have the potential to revolutionise healthcare by enabling early disease detection, real-time patient monitoring, and personalised treatments, a new study suggests. They are already saving lives...